Weak Identifiability in Models for Mark-Recapture-Recovery Data
作者： Olivier Gimenez , Byron J.T. Morgan , Stephen P. Brooks
DOI: 10.1007/978-0-387-78151-8_48
关键词:
摘要: The percentage overlap between prior and posterior distributions is obtained easily from the output of MCMC samplers. A 35% guideline for univariate marginal has been suggested as an indicator weak identifiability a parameter. As long uniform are adopted all model parameters, then found to work well range models mark-recapture-recovery data, where parameters probabilities. Its use illustrated on ring-recovery data male mallards, Cormack-Jolly-Seber capture-recapture dippers.
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